Map style transfer using pixel-to-pixel model

Abstract

The image style transfer is a well-known task and it is applied commonly in the field of artificial intelligence, which converts an image to an image with a specific style without modifying the image content and can be applied to many fields such as changing styled automatically for photos in the cellphone and map wrapping. Recent works focus on a general image style transfer. In this paper, we aim to solve the problem in a navigation application, which is to transfer the satellite maps into map images automatically by deep learning techniques. The methodology we choose for this project is a special GAN named pix2pix model. We decide to use the satellite images as our inputs for the model and let the corresponding Google map images be the output sources. Similar to a traditional GAN, we train the discriminator and generator simultaneously and we attempt to run the training process for 50 epochs in total. PNSR and SSIM are two features we are going to use to test the performance of our results. Finally, the accuracy needs to be improved.